Prepare a report analyzing land use and housing outcomes in one County (of your choice) in the Bay Area. You are welcome to include as many data-driven insights as you’d like, with the many kinds of housing and parcel datasets available from the Census Bureau and elsewhere, but at the minimum, you must include:
First I performed an analysis of housing burden on the two sub-populations of owners and renters. I calculated the fraction of owners and renters that experience housing burden, with a threshold of 30%, within San Francisco County specifically. I have also included maps of owner and renter housing burden across San Francisco County.
## [1] "Proportion of owners paying more than 30% of their income on housing"
## [1] 0.1071335
## [1] "Proportion of renters paying more than 30% of their income on housing"
## [1] 0.2263645
Next I broke up the owner sub-population into three sub-sub-populations based on race and ethnicity: one for white owners, one for Black owners, and one for Hispanic/Latino owners. I performed an analysis of housing burden on these sub-sub-populations. I calculated the fraction of these groups of owners that experience housing burden, with a threshold of 30%, within San Francisco County specifically. I have also included maps of each of these owner group’s housing burden across San Francisco County. I found that 8.56% of white owners, 9.16% of Black owners, and 7.8% of Hispanic/Latino owners experience housing burden.
I did the same for the renter sub-population, finding that 20.74% of white renters, 39.34% of Black renters, and 33.83% of Hispanic/Latino renters experience housing burden.
## [1] "Proportion of owners paying more than 30% of their income on housing"
## [1] 0.1071335
## [1] "Proportion of white owners paying more than 30% of their income on housing"
## [1] 0.08562461
## [1] "Proportion of Black owners paying more than 30% of their income on housing"
## [1] 0.09164389
## [1] "Proportion of Hispanic/Latino owners paying more than 30% of their income on housing"
## [1] 0.07786199
## [1] "Proportion of renters paying more than 30% of their income on housing"
## [1] 0.2263645
## [1] "Proportion of white renters paying more than 30% of their income on housing"
## [1] 0.2074027
## [1] "Proportion of Black renters paying more than 30% of their income on housing"
## [1] 0.3934407
## [1] "Proportion of Hispanic/Latino renters paying more than 30% of their income on housing"
## [1] 0.3382529
Below are the maps of owner housing burden overall, as well as white, Black, and Hispanic/Latino owner housing burden, respectively.
Below are the maps of renter housing burden overall, as well as white, Black, and Hispanic/Latino renter housing burden, respectively.
I have calculated and visualized the unused dwelling units for three census tracts in the Mission District in San Francisco. The tracts are: 020800, 020900, and 022803.
## [1] "pk.eyJ1IjoieGhhc2JhY2giLCJhIjoiY2toYXdjeGhvMTZ6OTJ0az#hsNWFkNnRhdSJ9.89v47Y3zHCcZ45pLzq4CKg"
## Reading layer `OGRGeoJSON' from data source `https://data.sfgov.org/api/geospatial/acdm-wktn?method=export&format=GeoJSON' using driver `GeoJSON'
## Simple feature collection with 232455 features and 22 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -122.5147 ymin: 37.70792 xmax: -122.3556 ymax: 37.83607
## geographic CRS: WGS 84
## [1] 225086
## [1] 213114
## [1] 224330
## [1] 174558
## Reading layer `h9wh-cg3m' from data source `https://data.sfgov.org/resource/h9wh-cg3m.geojson' using driver `GeoJSON'
## Simple feature collection with 1000 features and 2 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -122.5149 ymin: 37.70779 xmax: -122.357 ymax: 37.83062
## geographic CRS: WGS 84
## [1] 1421688
## [1] 589